{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 深度概率编程CVAE\n",
    "\n",
    "## 概述\n",
    "\n",
    "本例采用MindSpore的深度概率编程方法应用于条件变分自编码器(CVAE)模型训练。  \n",
    "整体流程如下：\n",
    "\n",
    "1. 数据集准备\n",
    "2. 定义条件变分自编码器网络；\n",
    "3. 定义损失函数和优化器；\n",
    "4. 训练生成模型。\n",
    "5. 生成新样本或重构输入样本。\n",
    "\n",
    "> 本例适用于GPU和Ascend环境。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据准备\n",
    "\n",
    "### 下载数据集\n",
    "\n",
    "本例使用MNIST_Data数据集，执行如下命令进行下载并解压到对应位置："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2020-12-18 10:55:35--  https://obs.dualstack.cn-north-4.myhuaweicloud.com/mindspore-website/notebook/datasets/MNIST_Data.zip\n",
      "Resolving proxy-notebook.modelarts-dev-proxy.com (proxy-notebook.modelarts-dev-proxy.com)... 192.168.0.172\n",
      "Connecting to proxy-notebook.modelarts-dev-proxy.com (proxy-notebook.modelarts-dev-proxy.com)|192.168.0.172|:8083... connected.\n",
      "Proxy request sent, awaiting response... 200 OK\n",
      "Length: 10754903 (10M) [application/zip]\n",
      "Saving to: ‘MNIST_Data.zip’\n",
      "\n",
      "MNIST_Data.zip      100%[===================>]  10.26M  49.3MB/s    in 0.2s    \n",
      "\n",
      "2020-12-18 10:55:35 (49.3 MB/s) - ‘MNIST_Data.zip’ saved [10754903/10754903]\n",
      "\n",
      "Archive:  MNIST_Data.zip\n",
      "   creating: ./datasets/MNIST_Data/test/\n",
      "  inflating: ./datasets/MNIST_Data/test/t10k-images-idx3-ubyte  \n",
      "  inflating: ./datasets/MNIST_Data/test/t10k-labels-idx1-ubyte  \n",
      "   creating: ./datasets/MNIST_Data/train/\n",
      "  inflating: ./datasets/MNIST_Data/train/train-images-idx3-ubyte  \n",
      "  inflating: ./datasets/MNIST_Data/train/train-labels-idx1-ubyte  \n",
      "./datasets/MNIST_Data/\n",
      "├── test\n",
      "│   ├── t10k-images-idx3-ubyte\n",
      "│   └── t10k-labels-idx1-ubyte\n",
      "└── train\n",
      "    ├── train-images-idx3-ubyte\n",
      "    └── train-labels-idx1-ubyte\n",
      "\n",
      "2 directories, 4 files\n"
     ]
    }
   ],
   "source": [
    "!wget -N https://obs.dualstack.cn-north-4.myhuaweicloud.com/mindspore-website/notebook/datasets/MNIST_Data.zip\n",
    "!unzip -o MNIST_Data.zip -d ./datasets\n",
    "!tree ./datasets/MNIST_Data/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据增强\n",
    "\n",
    "将数据集增强为适应CVAE网络训练要求的数据，本例主要是将原始图片像素大小由$28\\times28$增强为$32\\times32$，同时将多张图片组成1个`batch`来加速训练。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mindspore.common.dtype as mstype\n",
    "import mindspore.dataset as ds\n",
    "import mindspore.dataset.vision.c_transforms as CV\n",
    "\n",
    "\n",
    "def create_dataset(data_path, batch_size=32, repeat_size=1,\n",
    "                   num_parallel_workers=1):\n",
    "    \"\"\"\n",
    "    create dataset for train or test\n",
    "    \"\"\"\n",
    "    # define dataset\n",
    "    mnist_ds = ds.MnistDataset(data_path)\n",
    "\n",
    "    resize_height, resize_width = 32, 32\n",
    "    rescale = 1.0 / 255.0\n",
    "    shift = 0.0\n",
    "\n",
    "    # define map operations\n",
    "    resize_op = CV.Resize((resize_height, resize_width))  # Bilinear mode\n",
    "    rescale_op = CV.Rescale(rescale, shift)\n",
    "    hwc2chw_op = CV.HWC2CHW()\n",
    "\n",
    "    # apply map operations on images\n",
    "    mnist_ds = mnist_ds.map(operations=resize_op, input_columns=\"image\", num_parallel_workers=num_parallel_workers)\n",
    "    mnist_ds = mnist_ds.map(operations=rescale_op, input_columns=\"image\", num_parallel_workers=num_parallel_workers)\n",
    "    mnist_ds = mnist_ds.map(operations=hwc2chw_op, input_columns=\"image\", num_parallel_workers=num_parallel_workers)\n",
    "\n",
    "    # apply DatasetOps\n",
    "    mnist_ds = mnist_ds.batch(batch_size)\n",
    "    mnist_ds = mnist_ds.repeat(repeat_size)\n",
    "\n",
    "    return mnist_ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 定义条件变分自编码器网络\n",
    "\n",
    "变分自编码器的构成主要分为三个部分，编码器，解码器和隐空间。  \n",
    "其中：  \n",
    "编码器（Encoder）主要作用是将训练数据进行降维，压缩，提取特征，形成特征向量，存储在隐空间中。  \n",
    "解码器（Decoder）主要作用是将训练数据因空间分布的参数进行解码，还原生成出新的图像。  \n",
    "隐空间主要作用是将模型的特征按照某种分布特性进行存储，属于编码器和解码器中间的桥梁。  \n",
    "本例中条件变分自编码器（CVAE）是在变分自编码器的基础上增添标签训练，在后续随机采样生成图片的过程中，可以施加标签指定生成该条件的图片。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import mindspore.nn as nn\n",
    "from mindspore import context, Tensor\n",
    "import mindspore.ops as ops\n",
    "\n",
    "context.set_context(mode=context.GRAPH_MODE,device_target=\"GPU\")\n",
    "IMAGE_SHAPE=(-1,1,32,32)\n",
    "image_path = os.path.join(\"./datasets/MNIST_Data\",\"train\")\n",
    "\n",
    "class Encoder(nn.Cell):\n",
    "    def __init__(self, num_classes):\n",
    "        super(Encoder, self).__init__()\n",
    "        self.fc1 = nn.Dense(1024 + num_classes, 400)\n",
    "        self.relu = nn.ReLU()\n",
    "        self.flatten = nn.Flatten()\n",
    "        self.concat = ops.Concat(axis=1)\n",
    "        self.one_hot = nn.OneHot(depth=num_classes)\n",
    "\n",
    "    def construct(self, x, y):\n",
    "        x = self.flatten(x)\n",
    "        y = self.one_hot(y)\n",
    "        input_x = self.concat((x, y))\n",
    "        input_x = self.fc1(input_x)\n",
    "        input_x = self.relu(input_x)\n",
    "        return input_x\n",
    "\n",
    "class Decoder(nn.Cell):\n",
    "    def __init__(self):\n",
    "        super(Decoder, self).__init__()\n",
    "        self.fc2 = nn.Dense(400, 1024)\n",
    "        self.sigmoid = nn.Sigmoid()\n",
    "        self.reshape = ops.Reshape()\n",
    "\n",
    "    def construct(self, z):\n",
    "        z = self.fc2(z)\n",
    "        z = self.reshape(z, IMAGE_SHAPE)\n",
    "        z = self.sigmoid(z)\n",
    "        return z"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 定义优化器和损失函数\n",
    "\n",
    "定义条件变分自编码器的损失函数，将图像与label关联。  \n",
    "损失函数采用ELBO函数，此函数用于计算解码图像和原图像的差值，并通过对比两个图像的差值，以及图像分布的均值之差来计算两图的损失情况。  \n",
    "优化器采用`nn.Adam`来最小化损失值。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from mindspore.nn.probability.dpn import ConditionalVAE\n",
    "from mindspore.nn.probability.infer import ELBO, SVI\n",
    "\n",
    "class CVAEWithLossCell(nn.WithLossCell):\n",
    "    \"\"\"\n",
    "    Rewrite WithLossCell for CVAE\n",
    "    \"\"\"\n",
    "    def construct(self, data, label):\n",
    "        out = self._backbone(data, label)\n",
    "        return self._loss_fn(out, label)\n",
    "\n",
    "# define the encoder and decoder\n",
    "encoder = Encoder(num_classes=10)\n",
    "decoder = Decoder()\n",
    "# define the vae model\n",
    "cvae = ConditionalVAE(encoder, decoder, hidden_size=400, latent_size=20,num_classes=10)\n",
    "\n",
    "# define the loss function\n",
    "net_loss = ELBO(latent_prior='Normal', output_prior='Normal')\n",
    "# define the optimizer\n",
    "optimizer = nn.Adam(params=cvae.trainable_params(), learning_rate=0.001)\n",
    "net_with_loss = CVAEWithLossCell(cvae,net_loss)\n",
    "vi = SVI(net_with_loss=net_with_loss,optimizer=optimizer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "参数解释：\n",
    "\n",
    "- num_classes：类别数量，本例中为0-9个数字，共计10个种类。\n",
    "- ConditionalVAE：条件自编码器模型，将编码器，解码器，压缩大小，隐空间维度和类别数量等变分自编码器网络初始化。\n",
    "    - `encoder`：编码器网络。\n",
    "    - `decoder`：解码器网络。\n",
    "    - `hiddend_size`：数据压缩后的大小，本例为400。\n",
    "    - `latent_size`：隐空间的向量维度，向量维度越大，分别的特征维度越多，图像特征越清晰，本例中可调节维度大小为20。\n",
    "    - `num_classes`：类别数量。\n",
    "- ELBO：变分自编码器的损失函数。\n",
    "    - `latent_prior`：隐空间初始化分布，本例中隐空间的参数遵循正态分布。\n",
    "    - `output_prior`：输出权重的初始化分布，本例中其权重参数初始化分布遵循正态分布。\n",
    "- nn.Adam：优化器。\n",
    "- CVAEWithLossCell：本例重建了`nn.WithlossCell`函数，使得生成的数据，附带标签（label）。\n",
    "- SVI：模型函数，类似MindSpore中的Model，此函数为变分自编码器专用模型函数。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 训练生成模型\n",
    "\n",
    "生成训练数据，将调用上述代码中`vi`的训练模式，对模型进行训练，训练完成后打印出模型的loss值。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "39.697325069173175\n"
     ]
    }
   ],
   "source": [
    "# define the training dataset\n",
    "ds_train = create_dataset(image_path, 32, 1)\n",
    "# run the vi to return the trained network.\n",
    "cvae = vi.run(train_dataset=ds_train, epochs=5)\n",
    "# get the trained loss\n",
    "trained_loss = vi.get_train_loss()\n",
    "print(trained_loss)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 样本重建\n",
    "\n",
    "先定义可视化绘图函数`plot_image`，用于样本重建和条件采样生成数据的可视化。\n",
    "\n",
    "使用训练好的模型，查看重建数据的能力如何，这里取一组原始数据进行重建，执行如下代码："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The shape of the reconstructed sample is  (32, 1, 32, 32)\n",
      "\n",
      "=============The Original Images=============\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 32 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============The Reconstruct Images=============\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 32 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "def plot_image(sample_data,col_num=4,row_num=8,count=0):\n",
    "    for i in sample_data:\n",
    "        plt.subplot(col_num,row_num,count+1)\n",
    "        plt.imshow(np.squeeze(i.asnumpy()))\n",
    "        plt.axis(\"off\")\n",
    "        count += 1\n",
    "    plt.show()\n",
    "\n",
    "sample = next(ds_train.create_dict_iterator(output_numpy=True, num_epochs=1))\n",
    "sample_x = Tensor(sample['image'], dtype=mstype.float32)\n",
    "sample_y = Tensor(sample['label'], dtype=mstype.int32)\n",
    "reconstructed_sample = cvae.reconstruct_sample(sample_x, sample_y)\n",
    "print('The shape of the reconstructed sample is ', reconstructed_sample.shape)\n",
    "print(\"\\n=============The Original Images=============\")\n",
    "plot_image(sample_x)\n",
    "print(\"\\n============The Reconstruct Images=============\")\n",
    "plot_image(reconstructed_sample)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对比原图片，CVAE生成的图片能明显对应上原始图片，但还稍显模糊。说明训练效果已经达到但还有提升空间。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 条件样本采样\n",
    "\n",
    "在隐空间中进行条件采样，本例使用条件为`(0,1)`，对应生成`(0,1)`的图像数据，同时将采样生成的数据进行可视化。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The shape of the generated sample is  (32, 1, 32, 32)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 32 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# test function: generate_sample\n",
    "sample_label = Tensor([i for i in range(0,2)]*16, dtype=mstype.int32)\n",
    "# test function: generate_sample\n",
    "generated_sample = cvae.generate_sample(sample_label, 32, IMAGE_SHAPE)\n",
    "# test function: reconstruct_sample\n",
    "print('The shape of the generated sample is ', generated_sample.shape)\n",
    "plot_image(generated_sample,4,8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在条件为`(0,1)`特征采样中，生成的图片有的看起来像其他的数字，说明图像在特征分布中，其他数字的部分特征与`(0,1)`的特征出现了交叉，而随机采样正好采样到了这些交叉特征，导致`(0,1)`图片出现了其他数字的特征。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "MindSpore-1.0.1",
   "language": "python",
   "name": "mindspore-1.0.1"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}